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The MIANALYZE Procedure
Overview
Getting Started
Syntax
PROC MIANALYZE Statement
BY Statement
CLASS Statement
MODELEFFECTS Statement
STDERR Statement
TEST Statement
Details
Input Data Sets
Combining Inferences from Imputed Data Sets
Multiple Imputation Efficiency
Multivariate Inferences
Testing Linear Hypotheses about the Parameters
Examples of the Complete-Data Inferences
ODS Table Names
Examples
Reading Means and Standard Errors from a DATA= Data Set
Reading Means and Covariance Matrices from a DATA= COV Data Set
Reading Regression Results from a DATA= EST Data Set
Reading Mixed Model Results from PARMS= and COVB= Data Sets
Reading Generalized Linear Model Results
Reading GLM Results from PARMS= and XPXI= Data Sets
Reading Logistic Model Results from a PARMS= Data Set
Reading Mixed Model Results with Classification Covariates
Reading Nominal Logistic Model Results
Using a TEST statement
Combining Correlation Coefficients
Sensitivity Analysis with Control-Based Pattern Imputation
Sensitivity Analysis with Tipping-Point Approach
References
Details: MIANALYZE Procedure
Subsections:
Input Data Sets
Combining Inferences from Imputed Data Sets
Multiple Imputation Efficiency
Multivariate Inferences
Testing Linear Hypotheses about the Parameters
Examples of the Complete-Data Inferences
ODS Table Names
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